Diabetes is a major source of morbidity, mortality and economic expenses in the most countries. Although people with diabetes can prevent or delay complications associated with the disease by keeping blood glucose levels close to normal, preventing or delaying the development of the disease in the first place is as simple and for many researchers it is a sought after result.
Self-management has been shown to reduce the costs associated with diabetes. Improving glycemic control naturally results in improved quality of life, higher retained employment, greater productive capacity and less absenteeism. Numerous studies have shown that the most effective method of preventing long term complications of diabetes is by maintaining normal blood glucose levels. However, the on set of the disease could never be predicted. The majority of healthy people have no sigh or symptoms associated with diabetes. Symptoms can be so mild that even those actually suffering from the disease would not be aware of their condition until a complication of the disease erupts. Early detection of the disease has, therefore, been the holly grail of the diabetic research.
However, early detection of the disease could not simply rely on long term monitoring of blood glucose levels and would require analysis of the log term effects of everyday activities such as diet, physical activities and medications. By the same token, immediate monitoring of blood glucose by way of finger-stick test would not be effective in early detection of the disease or in controlling and maintaining normal blood glucose levels.
Thus, patients already suffering from diabetes and healthy individuals who are at risk face a problem of maintaining strict glycemic control in order to decrease the risk of complications or acquiring the disease. A major challenge is the creation of a simple and reliable non-invasive method for self-monitoring which relies on periodic measurements and which is capable of providing the patient and/or the physician with short-term information regarding the patient's glycemic management.
It is also highly recommended by the medical profession that insulin-treated individuals practice self-monitoring of blood glucose. Based on the level of glucose in the blood, the individual may take insulin dosage adjustments before injection. Adjustments are necessary since blood glucose levels vary on a daily basis for a variety of reasons. Despite the importance of self-monitoring, the proportion of individuals who self-monitor at least once a day declines significantly since obtaining blood from the finger is painful and often results in infection and formation of hard scar tissue.
One of the most clinically important sources of information regarding the blood-glucose levels of an individual comes from monitoring said individual for glycohemoglobin or hemoglobin A1c (AbA1c) level. An HbA1c result reflects the glucose concentration over the previous two to three months as weighted mean during that time. The HbA1c is used as an overall measure of extended glycemic control.
The utilization of the invasive HbA1c method in the prediction of blood glucose behavior is disclosed in International Publication WO 01/72208. Here, a method, a system and a computer program is disclosed for predicting the long term risk of hyperglycemia and the long-term and short-term risks of sever hyperglycemia in diabetes, based on glucose readings collected by a self-monitoring blood glucose device. The method and the system of the disclosed invention pertain directly to the enhancement of existing home blood glucose monitoring devices by introducing an intelligent data interpretation component capable of predicting both HbA1c and periods of risk of hyperglycemia.
WO 01/13786 discloses a method which utilizes blood glucose sampling, insulin infusion/injection records, heart rate information and heart rate variability information to predict blood glucose levels and the onset of hypoglycemia in the near future based on an assessed risk of hypoglycemia. This technique also provides for predicting blood glucose levels and for assessing the risk of the onset of hypoglycemia in the near future.
The assessment or prediction of the onset of hypoglycemia or hyperglycemia, nevertheless, is not relevant when it comes to individuals who are at high risk of developing diabetes or to patients suffering from the disease for whom self-monitoring is the preferred method.
U.S. Pat. No. 5,840,020 to Heinonen et al, disclose a method of such self-monitoring which comprises formulating an adaptive mathematical model about the behavior of a patients glucose level, the model taking into account the patient's diet, medication, and physical strain and comprising comparing the predictive values provided by the model to the measured glucose level.
A diabetes management system for predicting future blood glucose concentrations based upon current blood glucose concentrations and the insulin action remaining from previous insulin doses has been proposed in U.S. Pat. No. 5,822,715 to Worthington.